Evolving optimal parameters for swarm control

Using many inexpensive rovers in place of single costly ones is an idea that has been gaining attention in the last decade. How to effectively control this hardware is an open question, but because of its efficiency and distributed nature, swarming is an attractive option. While much research in the field investigates intelligent swarming, recent research has shown that the "unintelligent" swarm is an effective control mechanism for thoroughly covering a space and maintaining swarmlike behavior in the face of widespread failures. This paper takes that research one step further, exploring the application of a genetic algorithm to evolve optimal parameters for an exploratory swarm.